Magic Quadrant for Data Quality Tools
Data quality tools are vital for digital business transformation, especially now that many have emerging features like automation, machine learning, business-centric workflows and cloud deployment models. This Magic Quadrant assesses 15 vendors to help you make the best choice for your organization.
Digital transformation initiatives are putting new strain on data quality efforts as the data landscape becomes more complex and as new, urgent business requirements emerge. This strain is disrupting the market for data quality tools and increasing data quality requirements for buyers and sellers.
On the demand side, organizations are prioritizing four areas: audience, governance, data diversity and latency. On the supply side, data quality tool vendors also are prioritizing four areas: analytics, intelligence, deployment and pricing.
IBM
